This invention relates generally to accessing an unstructured knowledge base, and more particularly to improving the query and searching capability for accessing content in an unstructured enterprise knowledge base.
Wikis are simple web tools that enable users to collaboratively author content in a browser. They facilitate collecting and sharing knowledge in communities and enterprises, and their flexibility is ideal for managing content and processes that change frequently. However, this knowledge is unstructured and mostly contained in data entities within Wiki pages that are linked by title. Conventional Wiki systems do not enable knowledge reuse, and have only limited support for finding content. These limitations result from a lack of structure in the Wiki content. Almost all information is written in natural language which has little machine understandable semantics. For example, a page about the author John Grisham may contain a link to the page about his novel “The Pelican Brief”. The text may say that John Grisham wrote the Pelican Brief, but that information is not machine-understandable, and, therefore, cannot be used for querying, navigating, translating, or aggregating any information. More specifically, the existing Wiki systems do not offer structured access for browsing or searching information. Users cannot currently directly query a Wiki system for desired information, because the information content is unstructured. For example, users looking for “How old is John Grisham?”, “Who wrote the Pelican Brief?”, or “Which European authors have won the Nobel prize for literature?” cannot query the Wiki to ask these questions directly. Instead, they have to navigate to pages that contain the desired information and read it themselves. For more complicated queries that require some background knowledge, users need to manually combine the knowledge from several sources.
While Wiki allows users to easily make links from one page to other pages, these links can only be used to navigate to referenced pages. In fact, these explicit links are actually the only means of navigation. If no explicit connection is made between two related pages, e.g. between two authors that have the same publishing company, then no navigation will be possible between those pages, and there is no way to structure a query to locate the information directly.
Semantic Wiki was developed to extend conventional Wiki with “semantic technologies” like RDF and OWL to add more structure and facilitate structured queries and greater access to the knowledge content. This was done by giving users the ability to annotate existing navigational links with symbols that describe their meaning. Most annotations are mapped to simple OWL statements, similar to RDF triples. Annotations may add property and value information to pages. Properties are used to express binary relationships between one semantic entity (as represented by a Wiki page) and another such entity or data value. There are different kinds of values, such as other pages, strings, dates, locations, etc. While a regular Wiki enables users to make formal descriptions of resources using annotations in natural language, Semantic Wiki enables users to additionally describe resources in a formal language. Using the formal structured annotations of resources, Semantic Wiki allows a “semantic search” on the underlying knowledge base using queries expressed in a query language such as SPARQL which was proposed as a W3C recommendation for RDF querying. Users can search for information using structured queries, in addition to a simple full-text search, and can query the annotations directly or create views from such queries. Users can also find related information through associative browsing. The Wiki analyzes the semantic relations in the data and provides navigational links to related information.
Semantic Wiki annotations have advantages over regular Wiki solutions in that they also provide more information for better navigation between pages. Whereas a traditional Wiki can only follow a link, Semantic Wiki annotations offer additional information about the relation that the link describes, and this information can be used to afford additional or more sophisticated navigation. Semantic Wiki allows links to be annotated by giving them certain “types”. The idea behind this is that a link created by a user almost always carries meaning beyond mere navigation. Additionally, Semantic Wiki can change the way content is presented based on the semantic annotations. This can include enriching pages by displaying of semantically related pages, displaying of information that can be derived from the underlying knowledge, or even rendering the content of a page in a different manner that is more suitable for the context.
Although Semantic Wiki has greatly enhanced the ability to find and retrieve information from Wlki content, Semantic Wiki still requires using queries that syntactically and literally match annotations in the content to locate a page containing the information. It suffers from the inability to search for and locate content using structured queries that can be parsed to search the content based upon the intent of the user. Also, Semantic Wiki is unable to deduce facts that were not entered directly or to draw inferences automatically to locate information that was not literally requested. As a result, Semantic Wiki has limited utility for use in an unstructured knowledge base of an enterprise where multiple distributed enterprise users must have the ability to locate access and manage centrally stored information easily, and to collaborate with one another.
It is desirable to provide enhanced structure and querying capability to unstructured knowledge, such as in Semantic Wiki, to improve the ability of enterprise users, especially in a business context, to manage content, to allow use of more advanced structured searching to locate and use knowledge easily and efficiently, and to improve collaboration with other users in the enterprise. It is to these ends that the invention is directed.